
:orphan:

.. _sphx_glr_sg_execution_times:


Computation times
=================
**22:53.704** total execution time for 278 files **from all galleries**:

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  .. list-table::
   :header-rows: 1
   :class: table table-striped sg-datatable

   * - Example
     - Time
     - Mem (MB)
   * - :ref:`sphx_glr_auto_examples_feature_selection_plot_select_from_model_diabetes.py` (``../examples/feature_selection/plot_select_from_model_diabetes.py``)
     - 01:05.806
     - 0.0
   * - :ref:`sphx_glr_auto_examples_miscellaneous_plot_outlier_detection_bench.py` (``../examples/miscellaneous/plot_outlier_detection_bench.py``)
     - 00:56.835
     - 0.0
   * - :ref:`sphx_glr_auto_examples_compose_plot_compare_reduction.py` (``../examples/compose/plot_compare_reduction.py``)
     - 00:43.733
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_forest_hist_grad_boosting_comparison.py` (``../examples/ensemble/plot_forest_hist_grad_boosting_comparison.py``)
     - 00:43.474
     - 0.0
   * - :ref:`sphx_glr_auto_examples_manifold_plot_lle_digits.py` (``../examples/manifold/plot_lle_digits.py``)
     - 00:42.997
     - 0.0
   * - :ref:`sphx_glr_auto_examples_kernel_approximation_plot_scalable_poly_kernels.py` (``../examples/kernel_approximation/plot_scalable_poly_kernels.py``)
     - 00:41.185
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_tuned_decision_threshold.py` (``../examples/model_selection/plot_tuned_decision_threshold.py``)
     - 00:35.350
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_cost_sensitive_learning.py` (``../examples/model_selection/plot_cost_sensitive_learning.py``)
     - 00:33.020
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_learning_curve.py` (``../examples/model_selection/plot_learning_curve.py``)
     - 00:32.877
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_text_feature_extraction.py` (``../examples/model_selection/plot_grid_search_text_feature_extraction.py``)
     - 00:29.753
     - 0.0
   * - :ref:`sphx_glr_auto_examples_linear_model_plot_sgd_early_stopping.py` (``../examples/linear_model/plot_sgd_early_stopping.py``)
     - 00:29.427
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_randomized_search.py` (``../examples/model_selection/plot_randomized_search.py``)
     - 00:27.805
     - 0.0
   * - :ref:`sphx_glr_auto_examples_decomposition_plot_image_denoising.py` (``../examples/decomposition/plot_image_denoising.py``)
     - 00:27.506
     - 0.0
   * - :ref:`sphx_glr_auto_examples_inspection_plot_partial_dependence.py` (``../examples/inspection/plot_partial_dependence.py``)
     - 00:23.253
     - 0.0
   * - :ref:`sphx_glr_auto_examples_manifold_plot_compare_methods.py` (``../examples/manifold/plot_compare_methods.py``)
     - 00:22.607
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_stack_predictors.py` (``../examples/ensemble/plot_stack_predictors.py``)
     - 00:22.386
     - 0.0
   * - :ref:`sphx_glr_auto_examples_preprocessing_plot_target_encoder.py` (``../examples/preprocessing/plot_target_encoder.py``)
     - 00:21.865
     - 0.0
   * - :ref:`sphx_glr_auto_examples_manifold_plot_manifold_sphere.py` (``../examples/manifold/plot_manifold_sphere.py``)
     - 00:21.806
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_hgbt_regression.py` (``../examples/ensemble/plot_hgbt_regression.py``)
     - 00:20.613
     - 0.0
   * - :ref:`sphx_glr_auto_examples_linear_model_plot_poisson_regression_non_normal_loss.py` (``../examples/linear_model/plot_poisson_regression_non_normal_loss.py``)
     - 00:19.028
     - 0.0
   * - :ref:`sphx_glr_auto_examples_svm_plot_svm_scale_c.py` (``../examples/svm/plot_svm_scale_c.py``)
     - 00:18.718
     - 0.0
   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_8_0.py` (``../examples/release_highlights/plot_release_highlights_1_8_0.py``)
     - 00:18.545
     - 0.0
   * - :ref:`sphx_glr_auto_examples_manifold_plot_swissroll.py` (``../examples/manifold/plot_swissroll.py``)
     - 00:18.346
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_refit_callable.py` (``../examples/model_selection/plot_grid_search_refit_callable.py``)
     - 00:18.163
     - 0.0
   * - :ref:`sphx_glr_auto_examples_multiclass_plot_multiclass_overview.py` (``../examples/multiclass/plot_multiclass_overview.py``)
     - 00:18.118
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_cyclical_feature_engineering.py` (``../examples/applications/plot_cyclical_feature_engineering.py``)
     - 00:16.827
     - 0.0
   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_0_24_0.py` (``../examples/release_highlights/plot_release_highlights_0_24_0.py``)
     - 00:15.967
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_prediction_latency.py` (``../examples/applications/plot_prediction_latency.py``)
     - 00:14.681
     - 0.0
   * - :ref:`sphx_glr_auto_examples_miscellaneous_plot_kernel_ridge_regression.py` (``../examples/miscellaneous/plot_kernel_ridge_regression.py``)
     - 00:13.777
     - 0.0
   * - :ref:`sphx_glr_auto_examples_linear_model_plot_sparse_logistic_regression_mnist.py` (``../examples/linear_model/plot_sparse_logistic_regression_mnist.py``)
     - 00:13.606
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_topics_extraction_with_nmf_lda.py` (``../examples/applications/plot_topics_extraction_with_nmf_lda.py``)
     - 00:12.688
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_hdbscan.py` (``../examples/cluster/plot_hdbscan.py``)
     - 00:12.398
     - 0.0
   * - :ref:`sphx_glr_auto_examples_inspection_plot_linear_model_coefficient_interpretation.py` (``../examples/inspection/plot_linear_model_coefficient_interpretation.py``)
     - 00:11.722
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_permutation_tests_for_classification.py` (``../examples/model_selection/plot_permutation_tests_for_classification.py``)
     - 00:11.688
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_quantile.py` (``../examples/ensemble/plot_gradient_boosting_quantile.py``)
     - 00:10.855
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_time_series_lagged_features.py` (``../examples/applications/plot_time_series_lagged_features.py``)
     - 00:10.730
     - 0.0
   * - :ref:`sphx_glr_auto_examples_miscellaneous_plot_johnson_lindenstrauss_bound.py` (``../examples/miscellaneous/plot_johnson_lindenstrauss_bound.py``)
     - 00:10.622
     - 0.0
   * - :ref:`sphx_glr_auto_examples_linear_model_plot_tweedie_regression_insurance_claims.py` (``../examples/linear_model/plot_tweedie_regression_insurance_claims.py``)
     - 00:10.439
     - 0.0
   * - :ref:`sphx_glr_auto_examples_neural_networks_plot_mnist_filters.py` (``../examples/neural_networks/plot_mnist_filters.py``)
     - 00:10.212
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_digits.py` (``../examples/model_selection/plot_grid_search_digits.py``)
     - 00:10.207
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_oob.py` (``../examples/ensemble/plot_gradient_boosting_oob.py``)
     - 00:09.700
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_multi_metric_evaluation.py` (``../examples/model_selection/plot_multi_metric_evaluation.py``)
     - 00:09.564
     - 0.0
   * - :ref:`sphx_glr_auto_examples_inspection_plot_permutation_importance_multicollinear.py` (``../examples/inspection/plot_permutation_importance_multicollinear.py``)
     - 00:08.771
     - 0.0
   * - :ref:`sphx_glr_auto_examples_classification_plot_lda.py` (``../examples/classification/plot_lda.py``)
     - 00:08.370
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_out_of_core_classification.py` (``../examples/applications/plot_out_of_core_classification.py``)
     - 00:08.214
     - 0.0
   * - :ref:`sphx_glr_auto_examples_impute_plot_missing_values.py` (``../examples/impute/plot_missing_values.py``)
     - 00:08.137
     - 0.0
   * - :ref:`sphx_glr_auto_examples_decomposition_plot_faces_decomposition.py` (``../examples/decomposition/plot_faces_decomposition.py``)
     - 00:07.743
     - 0.0
   * - :ref:`sphx_glr_auto_examples_bicluster_plot_bicluster_newsgroups.py` (``../examples/bicluster/plot_bicluster_newsgroups.py``)
     - 00:07.734
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_digits_denoising.py` (``../examples/applications/plot_digits_denoising.py``)
     - 00:07.614
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_regularization.py` (``../examples/ensemble/plot_gradient_boosting_regularization.py``)
     - 00:07.571
     - 0.0
   * - :ref:`sphx_glr_auto_examples_text_plot_document_clustering.py` (``../examples/text/plot_document_clustering.py``)
     - 00:07.567
     - 0.0
   * - :ref:`sphx_glr_auto_examples_inspection_plot_permutation_importance.py` (``../examples/inspection/plot_permutation_importance.py``)
     - 00:07.447
     - 0.0
   * - :ref:`sphx_glr_auto_examples_mixture_plot_concentration_prior.py` (``../examples/mixture/plot_concentration_prior.py``)
     - 00:07.441
     - 0.0
   * - :ref:`sphx_glr_auto_examples_preprocessing_plot_all_scaling.py` (``../examples/preprocessing/plot_all_scaling.py``)
     - 00:07.439
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_successive_halving_heatmap.py` (``../examples/model_selection/plot_successive_halving_heatmap.py``)
     - 00:07.351
     - 0.0
   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_2_0.py` (``../examples/release_highlights/plot_release_highlights_1_2_0.py``)
     - 00:07.091
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_face_recognition.py` (``../examples/applications/plot_face_recognition.py``)
     - 00:06.994
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_species_distribution_modeling.py` (``../examples/applications/plot_species_distribution_modeling.py``)
     - 00:06.868
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_nested_cross_validation_iris.py` (``../examples/model_selection/plot_nested_cross_validation_iris.py``)
     - 00:06.650
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_forest_iris.py` (``../examples/ensemble/plot_forest_iris.py``)
     - 00:06.617
     - 0.0
   * - :ref:`sphx_glr_auto_examples_text_plot_document_classification_20newsgroups.py` (``../examples/text/plot_document_classification_20newsgroups.py``)
     - 00:06.393
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_successive_halving_iterations.py` (``../examples/model_selection/plot_successive_halving_iterations.py``)
     - 00:06.306
     - 0.0
   * - :ref:`sphx_glr_auto_examples_impute_plot_iterative_imputer_variants_comparison.py` (``../examples/impute/plot_iterative_imputer_variants_comparison.py``)
     - 00:06.063
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_model_complexity_influence.py` (``../examples/applications/plot_model_complexity_influence.py``)
     - 00:06.007
     - 0.0
   * - :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpr_noisy.py` (``../examples/gaussian_process/plot_gpr_noisy.py``)
     - 00:05.724
     - 0.0
   * - :ref:`sphx_glr_auto_examples_svm_plot_svm_regression.py` (``../examples/svm/plot_svm_regression.py``)
     - 00:05.689
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_cluster_comparison.py` (``../examples/cluster/plot_cluster_comparison.py``)
     - 00:05.572
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_categorical.py` (``../examples/ensemble/plot_gradient_boosting_categorical.py``)
     - 00:05.532
     - 0.0
   * - :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpc_iris.py` (``../examples/gaussian_process/plot_gpc_iris.py``)
     - 00:05.444
     - 0.0
   * - :ref:`sphx_glr_auto_examples_semi_supervised_plot_self_training_varying_threshold.py` (``../examples/semi_supervised/plot_self_training_varying_threshold.py``)
     - 00:05.334
     - 0.0
   * - :ref:`sphx_glr_auto_examples_linear_model_plot_sparse_logistic_regression_20newsgroups.py` (``../examples/linear_model/plot_sparse_logistic_regression_20newsgroups.py``)
     - 00:05.278
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_coin_segmentation.py` (``../examples/cluster/plot_coin_segmentation.py``)
     - 00:05.263
     - 0.0
   * - :ref:`sphx_glr_auto_examples_model_selection_plot_train_error_vs_test_error.py` (``../examples/model_selection/plot_train_error_vs_test_error.py``)
     - 00:05.170
     - 0.0
   * - :ref:`sphx_glr_auto_examples_semi_supervised_plot_semi_supervised_newsgroups.py` (``../examples/semi_supervised/plot_semi_supervised_newsgroups.py``)
     - 00:05.164
     - 0.0
   * - :ref:`sphx_glr_auto_examples_text_plot_hashing_vs_dict_vectorizer.py` (``../examples/text/plot_hashing_vs_dict_vectorizer.py``)
     - 00:05.127
     - 0.0
   * - :ref:`sphx_glr_auto_examples_gaussian_process_plot_compare_gpr_krr.py` (``../examples/gaussian_process/plot_compare_gpr_krr.py``)
     - 00:05.003
     - 0.0
   * - :ref:`sphx_glr_auto_examples_svm_plot_rbf_parameters.py` (``../examples/svm/plot_rbf_parameters.py``)
     - 00:04.898
     - 0.0
   * - :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpr_co2.py` (``../examples/gaussian_process/plot_gpr_co2.py``)
     - 00:04.736
     - 0.0
   * - :ref:`sphx_glr_auto_examples_applications_plot_stock_market.py` (``../examples/applications/plot_stock_market.py``)
     - 00:04.039
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_adaboost_multiclass.py` (``../examples/ensemble/plot_adaboost_multiclass.py``)
     - 00:03.826
     - 0.0
   * - :ref:`sphx_glr_auto_examples_neighbors_plot_digits_kde_sampling.py` (``../examples/neighbors/plot_digits_kde_sampling.py``)
     - 00:03.788
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_ensemble_oob.py` (``../examples/ensemble/plot_ensemble_oob.py``)
     - 00:03.558
     - 0.0
   * - :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_fa_model_selection.py` (``../examples/decomposition/plot_pca_vs_fa_model_selection.py``)
     - 00:03.473
     - 0.0
   * - :ref:`sphx_glr_auto_examples_neighbors_plot_species_kde.py` (``../examples/neighbors/plot_species_kde.py``)
     - 00:03.420
     - 0.0
   * - :ref:`sphx_glr_auto_examples_feature_selection_plot_rfe_digits.py` (``../examples/feature_selection/plot_rfe_digits.py``)
     - 00:03.341
     - 0.0
   * - :ref:`sphx_glr_auto_examples_miscellaneous_plot_anomaly_comparison.py` (``../examples/miscellaneous/plot_anomaly_comparison.py``)
     - 00:03.279
     - 0.0
   * - :ref:`sphx_glr_auto_examples_preprocessing_plot_discretization_classification.py` (``../examples/preprocessing/plot_discretization_classification.py``)
     - 00:03.276
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_birch_vs_minibatchkmeans.py` (``../examples/cluster/plot_birch_vs_minibatchkmeans.py``)
     - 00:03.205
     - 0.0
   * - :ref:`sphx_glr_auto_examples_calibration_plot_compare_calibration.py` (``../examples/calibration/plot_compare_calibration.py``)
     - 00:03.184
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_kmeans_digits.py` (``../examples/cluster/plot_kmeans_digits.py``)
     - 00:02.990
     - 0.0
   * - :ref:`sphx_glr_auto_examples_manifold_plot_t_sne_perplexity.py` (``../examples/manifold/plot_t_sne_perplexity.py``)
     - 00:02.950
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_inductive_clustering.py` (``../examples/cluster/plot_inductive_clustering.py``)
     - 00:02.874
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_gradient_boosting_early_stopping.py` (``../examples/ensemble/plot_gradient_boosting_early_stopping.py``)
     - 00:02.870
     - 0.0
   * - :ref:`sphx_glr_auto_examples_covariance_plot_robust_vs_empirical_covariance.py` (``../examples/covariance/plot_robust_vs_empirical_covariance.py``)
     - 00:02.731
     - 0.0
   * - :ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_training_curves.py` (``../examples/neural_networks/plot_mlp_training_curves.py``)
     - 00:02.676
     - 0.0
   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_4_0.py` (``../examples/release_highlights/plot_release_highlights_1_4_0.py``)
     - 00:02.634
     - 0.0
   * - :ref:`sphx_glr_auto_examples_calibration_plot_calibration_curve.py` (``../examples/calibration/plot_calibration_curve.py``)
     - 00:02.562
     - 0.0
   * - :ref:`sphx_glr_auto_examples_classification_plot_classification_probability.py` (``../examples/classification/plot_classification_probability.py``)
     - 00:02.482
     - 0.0
   * - :ref:`sphx_glr_auto_examples_compose_plot_column_transformer.py` (``../examples/compose/plot_column_transformer.py``)
     - 00:02.460
     - 0.0
   * - :ref:`sphx_glr_auto_examples_miscellaneous_plot_partial_dependence_visualization_api.py` (``../examples/miscellaneous/plot_partial_dependence_visualization_api.py``)
     - 00:02.437
     - 0.0
   * - :ref:`sphx_glr_auto_examples_ensemble_plot_feature_transformation.py` (``../examples/ensemble/plot_feature_transformation.py``)
     - 00:02.373
     - 0.0
   * - :ref:`sphx_glr_auto_examples_linear_model_plot_elastic_net_precomputed_gram_matrix_with_weighted_samples.py` (``../examples/linear_model/plot_elastic_net_precomputed_gram_matrix_with_weighted_samples.py``)
     - 00:02.339
     - 0.0
   * - :ref:`sphx_glr_auto_examples_neural_networks_plot_rbm_logistic_classification.py` (``../examples/neural_networks/plot_rbm_logistic_classification.py``)
     - 00:02.205
     - 0.0
   * - :ref:`sphx_glr_auto_examples_covariance_plot_lw_vs_oas.py` (``../examples/covariance/plot_lw_vs_oas.py``)
     - 00:02.188
     - 0.0
   * - :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpc.py` (``../examples/gaussian_process/plot_gpc.py``)
     - 00:02.140
     - 0.0
   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_0_22_0.py` (``../examples/release_highlights/plot_release_highlights_0_22_0.py``)
     - 00:02.130
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_face_compress.py` (``../examples/cluster/plot_face_compress.py``)
     - 00:02.096
     - 0.0
   * - :ref:`sphx_glr_auto_examples_cluster_plot_ward_structured_vs_unstructured.py` (``../examples/cluster/plot_ward_structured_vs_unstructured.py``)
     - 00:02.094
     - 0.0
   * - :ref:`sphx_glr_auto_examples_classification_plot_classifier_comparison.py` (``../examples/classification/plot_classifier_comparison.py``)
     - 00:02.067
     - 0.0
   * - :ref:`sphx_glr_auto_examples_decomposition_plot_pca_iris.py` (``../examples/decomposition/plot_pca_iris.py``)
     - 00:02.060
     - 0.0
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     - 00:01.934
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     - 00:01.928
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     - 00:01.870
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     - 00:01.826
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     - 00:01.792
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   * - :ref:`sphx_glr_auto_examples_cluster_plot_linkage_comparison.py` (``../examples/cluster/plot_linkage_comparison.py``)
     - 00:01.780
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   * - :ref:`sphx_glr_auto_examples_neural_networks_plot_mlp_alpha.py` (``../examples/neural_networks/plot_mlp_alpha.py``)
     - 00:01.736
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     - 00:01.730
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     - 00:01.721
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     - 00:01.701
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     - 00:01.647
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     - 00:01.630
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     - 00:01.557
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     - 00:01.491
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   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_3_0.py` (``../examples/release_highlights/plot_release_highlights_1_3_0.py``)
     - 00:01.475
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     - 00:01.356
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     - 00:01.304
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     - 00:01.240
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     - 00:01.188
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     - 00:01.176
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     - 00:01.145
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     - 00:01.112
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     - 00:01.091
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     - 00:01.084
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     - 00:01.056
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     - 00:01.035
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     - 00:00.978
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     - 00:00.973
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     - 00:00.968
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     - 00:00.967
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     - 00:00.934
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     - 00:00.917
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     - 00:00.905
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     - 00:00.828
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     - 00:00.803
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     - 00:00.802
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     - 00:00.760
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     - 00:00.755
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     - 00:00.727
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     - 00:00.715
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     - 00:00.694
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     - 00:00.685
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     - 00:00.647
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     - 00:00.623
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     - 00:00.581
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     - 00:00.570
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     - 00:00.562
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     - 00:00.553
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     - 00:00.539
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     - 00:00.534
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     - 00:00.514
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     - 00:00.513
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     - 00:00.495
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     - 00:00.482
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     - 00:00.470
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     - 00:00.462
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     - 00:00.461
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     - 00:00.456
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     - 00:00.445
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     - 00:00.440
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     - 00:00.436
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     - 00:00.428
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     - 00:00.425
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     - 00:00.425
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   * - :ref:`sphx_glr_auto_examples_semi_supervised_plot_label_propagation_digits_active_learning.py` (``../examples/semi_supervised/plot_label_propagation_digits_active_learning.py``)
     - 00:00.418
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   * - :ref:`sphx_glr_auto_examples_linear_model_plot_logistic_l1_l2_sparsity.py` (``../examples/linear_model/plot_logistic_l1_l2_sparsity.py``)
     - 00:00.413
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     - 00:00.408
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     - 00:00.406
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     - 00:00.406
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     - 00:00.402
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     - 00:00.401
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     - 00:00.395
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     - 00:00.394
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     - 00:00.379
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     - 00:00.369
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     - 00:00.366
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     - 00:00.366
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     - 00:00.362
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     - 00:00.338
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     - 00:00.338
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     - 00:00.335
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     - 00:00.322
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     - 00:00.320
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     - 00:00.320
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     - 00:00.310
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     - 00:00.300
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     - 00:00.297
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     - 00:00.297
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     - 00:00.263
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     - 00:00.260
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     - 00:00.260
     - 0.0
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     - 00:00.259
     - 0.0
   * - :ref:`sphx_glr_auto_examples_semi_supervised_plot_label_propagation_digits.py` (``../examples/semi_supervised/plot_label_propagation_digits.py``)
     - 00:00.258
     - 0.0
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     - 00:00.254
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   * - :ref:`sphx_glr_auto_examples_cluster_plot_affinity_propagation.py` (``../examples/cluster/plot_affinity_propagation.py``)
     - 00:00.254
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     - 00:00.247
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     - 00:00.245
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     - 00:00.242
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     - 00:00.225
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   * - :ref:`sphx_glr_auto_examples_mixture_plot_gmm.py` (``../examples/mixture/plot_gmm.py``)
     - 00:00.216
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     - 00:00.207
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     - 00:00.198
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   * - :ref:`sphx_glr_auto_examples_neighbors_plot_classification.py` (``../examples/neighbors/plot_classification.py``)
     - 00:00.193
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     - 00:00.183
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     - 00:00.182
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     - 00:00.180
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   * - :ref:`sphx_glr_auto_examples_linear_model_plot_multi_task_lasso_support.py` (``../examples/linear_model/plot_multi_task_lasso_support.py``)
     - 00:00.179
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     - 00:00.179
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     - 00:00.178
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   * - :ref:`sphx_glr_auto_examples_linear_model_plot_omp.py` (``../examples/linear_model/plot_omp.py``)
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   * - :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_lda.py` (``../examples/decomposition/plot_pca_vs_lda.py``)
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   * - :ref:`sphx_glr_auto_examples_svm_plot_iris_svc.py` (``../examples/svm/plot_iris_svc.py``)
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   * - :ref:`sphx_glr_auto_examples_cross_decomposition_plot_compare_cross_decomposition.py` (``../examples/cross_decomposition/plot_compare_cross_decomposition.py``)
     - 00:00.162
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     - 00:00.162
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   * - :ref:`sphx_glr_auto_examples_cluster_plot_mini_batch_kmeans.py` (``../examples/cluster/plot_mini_batch_kmeans.py``)
     - 00:00.160
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   * - :ref:`sphx_glr_auto_examples_miscellaneous_plot_multilabel.py` (``../examples/miscellaneous/plot_multilabel.py``)
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     - 00:00.152
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   * - :ref:`sphx_glr_auto_examples_svm_plot_linearsvc_support_vectors.py` (``../examples/svm/plot_linearsvc_support_vectors.py``)
     - 00:00.152
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     - 00:00.146
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   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_7_0.py` (``../examples/release_highlights/plot_release_highlights_1_7_0.py``)
     - 00:00.144
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   * - :ref:`sphx_glr_auto_examples_cluster_plot_dbscan.py` (``../examples/cluster/plot_dbscan.py``)
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     - 00:00.135
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     - 00:00.131
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   * - :ref:`sphx_glr_auto_examples_miscellaneous_plot_set_output.py` (``../examples/miscellaneous/plot_set_output.py``)
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   * - :ref:`sphx_glr_auto_examples_neighbors_plot_nca_illustration.py` (``../examples/neighbors/plot_nca_illustration.py``)
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     - 00:00.121
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   * - :ref:`sphx_glr_auto_examples_datasets_plot_random_multilabel_dataset.py` (``../examples/datasets/plot_random_multilabel_dataset.py``)
     - 00:00.118
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   * - :ref:`sphx_glr_auto_examples_svm_plot_oneclass.py` (``../examples/svm/plot_oneclass.py``)
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   * - :ref:`sphx_glr_auto_examples_gaussian_process_plot_gpc_isoprobability.py` (``../examples/gaussian_process/plot_gpc_isoprobability.py``)
     - 00:00.117
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   * - :ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py` (``../examples/tree/plot_unveil_tree_structure.py``)
     - 00:00.114
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   * - :ref:`sphx_glr_auto_examples_cluster_plot_digits_agglomeration.py` (``../examples/cluster/plot_digits_agglomeration.py``)
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   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_6_0.py` (``../examples/release_highlights/plot_release_highlights_1_6_0.py``)
     - 00:00.106
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     - 00:00.092
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   * - :ref:`sphx_glr_auto_examples_linear_model_plot_huber_vs_ridge.py` (``../examples/linear_model/plot_huber_vs_ridge.py``)
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     - 00:00.086
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     - 00:00.081
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     - 00:00.077
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   * - :ref:`sphx_glr_auto_examples_cluster_plot_agglomerative_dendrogram.py` (``../examples/cluster/plot_agglomerative_dendrogram.py``)
     - 00:00.073
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   * - :ref:`sphx_glr_auto_examples_neighbors_plot_lof_outlier_detection.py` (``../examples/neighbors/plot_lof_outlier_detection.py``)
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     - 00:00.063
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     - 00:00.060
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     - 00:00.059
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     - 00:00.053
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     - 00:00.052
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   * - :ref:`sphx_glr_auto_examples_linear_model_plot_nnls.py` (``../examples/linear_model/plot_nnls.py``)
     - 00:00.051
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     - 00:00.050
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   * - :ref:`sphx_glr_auto_examples_frozen_plot_frozen_examples.py` (``../examples/frozen/plot_frozen_examples.py``)
     - 00:00.017
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   * - :ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_0_0.py` (``../examples/release_highlights/plot_release_highlights_1_0_0.py``)
     - 00:00.016
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   * - :ref:`sphx_glr_auto_examples_feature_selection_plot_feature_selection_pipeline.py` (``../examples/feature_selection/plot_feature_selection_pipeline.py``)
     - 00:00.016
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   * - :ref:`sphx_glr_auto_examples_applications_wikipedia_principal_eigenvector.py` (``../examples/applications/wikipedia_principal_eigenvector.py``)
     - 00:00.000
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   * - :ref:`sphx_glr_auto_examples_developing_estimators_sklearn_is_fitted.py` (``../examples/developing_estimators/sklearn_is_fitted.py``)
     - 00:00.000
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